GAR-Font is a global-aware autoregressive framework for multimodal few-shot font generation that adds global tokenization, a language-style adapter, and post-refinement to improve style coherence over patch-based methods.
Dg- font: Deformable generative networks for unsupervised font generation
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DRG-Font generates stylistically consistent glyphs from few references by decomposing style and content via contrastive disentanglement, dynamic reference selection, and multi-scale fusion blocks.
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Beyond Patches: Global-aware Autoregressive Model for Multimodal Few-Shot Font Generation
GAR-Font is a global-aware autoregressive framework for multimodal few-shot font generation that adds global tokenization, a language-style adapter, and post-refinement to improve style coherence over patch-based methods.
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DRG-Font: Dynamic Reference-Guided Few-shot Font Generation via Contrastive Style-Content Disentanglement
DRG-Font generates stylistically consistent glyphs from few references by decomposing style and content via contrastive disentanglement, dynamic reference selection, and multi-scale fusion blocks.